An uncertainty-aware precision grasping process for objects with unknown dimensions

Reliable precision grasping is a pre-condition for manipulation tasks e.g. in assembly and packaging tasks. Especially for small and light objects robust grasping is extremely challenging since even slight errors in the object pose or dimensions lead to irreparable failures caused by unintended finger-object contacts. State of the art techniques address the problem of grasping in the presence of uncertainty only at the grasp planning stage. We regard grasping as a dynamic process that needs closed loop control to be robustly executed, and propose an approach to robustly perform precision grasps despite of the significant perceptual and actuation uncertainties we have to face in reality. We conduct extensive real world experiments with light and fragile objects of unknown dimensions. The result confirms that our uncertainty-aware closed-loop approach significantly improves the robustness.